FAILED - The request to create an MLModel didn't run to
completion. The model isn't usable.

COMPLETED - The creation process completed successfully.

DELETED - The MLModel is marked as deleted. It isn't
usable.

Type: String

Valid Values: PENDING | INPROGRESS | FAILED | COMPLETED | DELETED

Required: No

TrainingDataSourceId

The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 64.

Pattern: [a-zA-Z0-9_.-]+

Required: No

TrainingParameters

A list of the training parameters in the MLModel. The list is implemented as
a map of key-value pairs.

The following is the current set of training parameters:

sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending on the
input data, the size of the model might affect its performance.

The value is an integer that ranges from 100000 to 2147483648. The default value is 33554432.

sgd.maxPasses - The number of times that the training process traverses the
observations to build the MLModel. The value is an integer that
ranges from 1 to 100. The default value is
10.

sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling the data
improves a model's ability to find the optimal solution for a variety of data
types. The valid values are auto and none. The default
value is none.

sgd.l1RegularizationAmount - The coefficient regularization L1 norm, which controls
overfitting the data by penalizing large coefficients. This parameter tends to
drive coefficients to zero, resulting in sparse feature set. If you use this
parameter, start by specifying a small value, such as 1.0E-08.

The value is a double that ranges from 0 to MAX_DOUBLE.
The default is to not use L1 normalization. This parameter can't be used when
L2 is specified. Use this parameter sparingly.

sgd.l2RegularizationAmount - The coefficient regularization L2 norm, which controls
overfitting the data by penalizing large coefficients. This tends to drive
coefficients to small, nonzero values. If you use this parameter, start by
specifying a small value, such as 1.0E-08.

The value is a double that ranges from 0 to MAX_DOUBLE.
The default is to not use L2 normalization. This parameter can't be used when
L1 is specified. Use this parameter sparingly.

Type: String to string map

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs,
see the following: